Enhanced Sampling of Ligand Binding Coupled to RNA Conformational Dynamics

Noncoding RNAs have recently emerged as promising targets for therapeutic drugs. However, their high conformational flexibility presents significant challenges in structure-based rational drug discovery. Therefore, it is essential to gain detailed mechanistic insights into the millisecond-timescale ligand recognition process coupled to the conformational dynamics of RNA. Enhanced sampling simulations can help investigate these intricate dynamical processes by effectively exploring the rugged conformational landscapes of RNA-ligand complexes. In this study, we applied the On-the-fly Probability Enhanced Sampling (OPES) algorithm and its flooding variant to compute the free energy surface, kinetics, and binding mechanism for three different natural and synthetic ligands to a prototypical RNA aptamer. Our simulations revealed the dynamic coupling between ligand recognition and the base-flipping transition of a cytosine (C27) nucleotide. In addition to reproducing the relative trends of binding affinities and residence times, our results uncovered a competing effect between the conformational selection and the induced fit mechanisms. The preference for one mechanism over the other is influenced by the binding affinity. By integrating these mechanistic insights with the binding affinity and kinetics derived from our simulations, we provide an atomistically detailed understanding of the RNA-ligand recognition process.